In vivo identification of apoptotic and extracellular vesicle-bound live cells using image-based deep learning.
J Extracell Vesicles. 2020 Jul 16;9(1):1792683. doi: 10.1080/20013078.2020.1792683. PMID: 32944180; PMCID: PMC7480589.
| Authors/Editors: | Kranich J, Chlis NK, Rausch L, Latha A, Schifferer M, Kurz T, Foltyn-Arfa Kia A, Simons M, Theis FJ, Brocker T. |
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| Publication Date: | 2020 |
Abstract
The in vivo detection of dead cells remains a major challenge due to technical hurdles. Here, we present a novel method, where injection of fluorescent milk fat globule-EGF factor 8 protein (MFG-E8) in vivo combined with imaging flow cytometry and deep learning allows the identification of dead cells based on their surface exposure of phosphatidylserine (PS) and other image parameters. A convolutional autoencoder (CAE) was trained on defined pictures and successfully used to identify apoptotic cells in vivo. However, unexpectedly, these analyses also revealed that the great majority of PS+ cells were not apoptotic, but rather live cells associated with PS+ extracellular vesicles (EVs). During acute viral infection apoptotic cells increased slightly, while up to 30% of lymphocytes were decorated with PS+ EVs of antigen-presenting cell (APC) exosomal origin. The combination of recombinant fluorescent MFG-E8 and the CAE-method will greatly facilitate analyses of cell death and EVs in vivo.
KEYWORDS: Extracellular Vesicles, exosomes, dendritic cells, viral Infection, irradiation, apoptosis
